FINAL Study Guide

# FINAL Study Guide - FINAL EXAM I Factorial Designs a...

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FINAL EXAM I. Factorial Designs a) Definition i) Any experimental design with more than one independent variable ii) Example (1) IV #1 Concrete vs. Abstract words --- 2 variables (2) IV #2 Recall vs. Recognition --- 2 types of tests (a) Could have two experiments Experiment #1 Experiment #2 Concrete Abstract Recall 1 2 (i) Problem 1. Could make one experiment --- Factorial Matrix Concrete Abstract Recall 1 2 Recognition 3 4 b) Factorial Matrix i) A row and column arrangement that characterizes a factorial design and shows the independent variables, the levels of each independent variable, and the total number of conditions (cells) in the study (1) Levels of the IV are NOT the same as the conditions (a) Example: (i) IV level: Concrete (ii) Condition: Concrete recall c) Notation for factorial designs i) Simultaneously identifies the number of independent variables and the number of levels of each variable ii) Example (1) 2 x 2 factorial design (a) The two numbers shows how many IVs there are (b) The first number shows the number of levels of IV #1 (word type) (c) The second number shows the number of levels of IV #2 (test type) (2) 2 x 2 x 2 factorial design (a) There are 3 IVs each with 2 levels (3) 2 x 4 x 3 x 4 (a) There are 4 IVs, the first has 2 levels, the second has 4 levels, etc. (4) THE ORDER OF THE NUMBERS DOESN’T MATTER iii) How to tell how many conditions there are by looking at the notation only (1) The number of conditions in any factorial can be determined simply by calculating the product of the numbers in the notation system (2) Example (a) 3 x 3 factorial design = 9 conditions (b) 2 x 2 x 2 factorial design = 8 conditions d) Building a factorial matrix with more then 2 IVs C1 B1 B2 A1 A1B1C1 A1B2C1 Concrete Abstract Recognition 1 2

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A2 A2B1C1 A2B2C1 i) HAS ALL 8 CONDITIONS ii) These don’t normally work very well with larger factorial designs e) MOST STUDIES HAVE MORE THAN ONE IV AND THUS USE FACTORIAL DESIGNS f) Advantages of factorial designs i) The effects of the independent variables can be examined separately and in combination (1) Individual effects of each independent variables --- MAIN EFFECTS (2) Interactions between the independent variables --- INTERACTIONS g) Main Effects i) Refer to whether or not significant differences exist between the levels of an independent variable and a factorial design Concrete Abstract Recall 1 2 Recognition 3 4 (1) HOW MANY MAIN EFFECTS COULD I HAVE? (a) As many as the number of IVs in the study (b) Example (i) Above there are two main effects (word type and test type) ii) How to tell if there is a main effect (1) Steps: (a) Combine all the data for each of the levels of each IV (b) Compare the data between the levels of the IV Concrete Abstract Recall 10 20 Mean=15 Recognition 25 15 Mean=20 (i) IT SEEMS THAT THERE MAY BE A MAIN EFFECT FOR TEST TYPE Concrete Abstract Recall 10 20 Recognition 25 15 Mean=17.5 Mean=17.5 (ii) IT SEEMS LIKE THERE ISN’T A MAIN EFFECT FOR WORD TYPE h) Interactions i) In a factorial design, occurs when the effect of one independent variable depends on the level of another independent variable Concrete Abstract
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• Fall '06
• Friedrich
• Correlation and dependence, Pearson product-moment correlation coefficient, Spearman's rank correlation coefficient, factorial design, Correlational Research

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FINAL Study Guide - FINAL EXAM I Factorial Designs a...

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